CFinder: locating cliques and overlapping modules in biological networks. Summary: Most cellular tasks are performed not by individual proteins, but by groups of functionally associated proteins, often referred to as modules. In a protein assocation network modules appear as groups of densely interconnected nodes, also called communities or clusters. These modules often overlap with each other and form a network of their own, in which nodes (links) represent the modules (overlaps). We introduce CFinder, a fast program locating and visualizing overlapping, densely interconnected groups of nodes in undirected graphs, and allowing the user to easily navigate between the original graph and the web of these groups. We show that in gene (protein) association networks CFinder can be used to predict the function(s) of a single protein and to discover novel modules. CFinder is also very efficient for locating the cliques of large sparse graphs. Availability: CFinder (for Windows, Linux and Macintosh) and its manual can be downloaded from Supplementary information: Supplementary data are available on Bioinformatics online.

References in zbMATH (referenced in 19 articles )

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  1. Rasti, Saeid; Vogiatzis, Chrysafis: A survey of computational methods in protein-protein interaction networks (2019)
  2. Yu, Yang; Zheng, Zeyu: Protein complex identification based on weighted PPI network with multi-source information (2019)
  3. Liu, Wei; Ma, Liangyu; Jeon, Byeungwoo; Chen, Ling; Chen, Bolun: A network hierarchy-based method for functional module detection in protein-protein interaction networks (2018)
  4. Song, Wei; Liu, Huaping; Wang, Jiajia; Kong, Yan; Yin, Xia; Zang, Weidong: MATHT: a web server for comprehensive transcriptome data analysis (2018)
  5. Ozogány, Katalin; Vicsek, Tamás: Modeling the emergence of modular leadership hierarchy during the collective motion of herds made of harems (2015)
  6. Kasabov, Nikola (ed.): Springer handbook of bio-/neuro-informatics (2014)
  7. Mascia, Franco; Pellegrini, Paola; Birattari, Mauro; Stützle, Thomas: An analysis of parameter adaptation in reactive tabu search (2014)
  8. Tóth, Bálint; Vicsek, Tamás; Palla, Gergely: Overlapping modularity at the critical point of (k)-clique percolation (2013)
  9. Ma, Xiaoke; Gao, Lin: Predicting protein complexes in protein interaction networks using a core-attachment algorithm based on graph communicability (2012) ioport
  10. Pirim, Harun; Ekåioälu, Burak; Perkins, Andy D.; Yüceer, Çetin: Clustering of high throughput gene expression data (2012)
  11. Yu, Liang; Gao, Lin; Li, Kui; Zhao, Yi; Chiu, David K. Y.: A degree-distribution based hierarchical agglomerative clustering algorithm for protein complexes identification (2011) ioport
  12. Vijayabaskar, M. S.; Vishveshwara, Saraswathi: Comparative analysis of thermophilic and mesophilic proteins using protein energy networks (2010) ioport
  13. Macropol, Kathy; Can, Tolga; Singh, Ambuj K.: RRW: repeated random walks on genome-scale protein networks for local cluster discovery (2009) ioport
  14. Matsunaga, Tsutomu; Yonemori, Chikara; Tomita, Etsuji; Muramatsu, Masaaki: Clique-based data mining for related genes in a biomedical database (2009) ioport
  15. Wei, Fang; Qian, Weining; Wang, Chen; Zhou, Aoying: Detecting overlapping community structures in networks (2009) ioport
  16. Wong, Limsoon; Liu, Guimei: Protein interactome analysis for countering pathogen drug resistance (2009) ioport
  17. Zhang, Shihua; Wang, Rui-Sheng; Zhang, Xiang-Sun; Chen, Luonan: Fuzzy system methods in modeling gene expression and analyzing protein networks (2009)
  18. Adamcsek, Balázs; Palla, Gergely; Farkas, Illés J.; Derényi, Imre; Vicsek, Tamás: Cfinder: Locating cliques and overlapping modules in biological networks (2006) ioport
  19. Zhang, Shihua; Ning, Xuemei; Zhang, Xiangsun: Identification of functional modules in a PPI network by clique percolation clustering (2006)